6  Further Resources

6.1 Context Clues for $200

This collection lets you explore, visualize, and make sense of data beyond the basics

If you want a little more practice or a different explanation style, these are good places to keep going. The goal here is not to overload you. It is to give you a few reliable places to revisit the same ideas from a different angle.

flowchart LR
    A["Nominal"] --> B["Counts / proportions"]
    C["Ordinal"] --> D["Ordered counts / threshold shares"]
    E["Discrete"] --> F["Counts / rates"]
    G["Continuous"] --> H["Means / medians / histograms"]

External resources

• Guide to Data Types and How to Graph Them in Statistics
  A plain-language reference for nominal, ordinal, discrete, and continuous data.

• CDC Field Epidemiology Manual: Describing Epidemiologic Data
  Useful once you want to see how variable type connects to real epidemiologic description.

• CDC NHANES Interactive Data Visualizations
  A good example of how public-health variables get summarized and displayed in practice.

• Data Carpentry: Data visualization with ggplot2
  Helpful if you want more exposure to how plot choice follows the structure of the data.